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000022370 084__ $$2WoS$$aMeteorology & Atmospheric Sciences
000022370 1001_ $$0P:(DE-Juel1)VDB1549$$aSpang, R.$$b0$$uFZJ
000022370 245__ $$aFast cloud parameter retrievals of MIPAS/Envisat
000022370 260__ $$aKatlenburg-Lindau$$bEGU$$c2012
000022370 300__ $$a7135 - 7164
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000022370 440_0 $$09601$$aAtmospheric Chemistry and Physics$$v12$$x1680-7316$$y15
000022370 500__ $$3POF3_Assignment on 2016-02-29
000022370 500__ $$aThe authors gratefully acknowledge S. P. Palm (Science Systems and Applications Inc., Lanham, Maryland, USA) and J.D. Spinhirne (NASA, Goddard Space Flight Centre) for providing GLAS data as well as P. H. Wang (Science and Technology Corporation) for preparing and providing the SAGE II V6 data. The Oxford authors acknowledge support from the UK National Centre for Earth Observation. R. Spang would like to thank S. Rohs (Forschungszentrum Julich) for support in the validation activities of SAGE II, and R. Muller (Forschungszentrum Julich) for discussions on the scientific objectives of the manuscript. Part of this work was supported by ESA through the MIPclouds project: "Cloud Information Retrieval from MIPAS Measurements", AO/1-5255/06/I-OL.
000022370 520__ $$aThe infrared limb spectra of the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) on board the Envisat satellite include detailed information on tropospheric clouds and polar stratospheric clouds (PSC). However, no consolidated cloud product is available for the scientific community. Here we describe a fast prototype processor for cloud parameter retrieval from MIPAS (MIP-clouds). Retrieval of parameters such as cloud top height, temperature, and extinction are implemented, as well as retrieval of microphysical parameters, e. g. effective radius and the integrated quantities over the limb path (surface area density and volume density). MIPclouds classifies clouds as either liquid or ice cloud in the upper troposphere and polar stratospheric clouds types in the stratosphere based on statistical combinations of colour ratios and brightness temperature differences.Comparison of limb measurements of clouds with model results or cloud parameters from nadir looking instruments is often difficult due to different observation geometries. We therefore introduce a new concept, the limb-integrated surface area density path (ADP). By means of validation and radiative transfer calculations of realistic 2-D cloud fields as input for a blind test retrieval (BTR), we demonstrate that ADP is an extremely valuable parameter for future comparison with model data of ice water content, when applying limb integration (ray tracing) through the model fields. In addition, ADP is used for a more objective definition of detection thresholds of the applied detection methods. Based on BTR, a detection threshold of ADP = 10(7) mu m(2) cm(-2) and an ice water content of 10(-5) gm(-3) is estimated, depending on the horizontal and vertical extent of the cloud.Intensive validation of the cloud detection methods shows that the limb-sounding MIPAS instrument has a sensitivity in detecting stratospheric and tropospheric clouds similar to that of space-and ground-based lidars, with a tendency for higher cloud top heights and consequently higher sensitivity for some of the MIPAS detection methods. For the high cloud amount (HCA, pressure levels below 440 hPa) on global scales the sensitivity of MIPAS is significantly greater than that of passive nadir viewers. This means that the high cloud fraction will be underestimated in the ISCCP dataset compared to the amount of high clouds deduced by MIPAS. Good correspondence in seasonal variability and geographical distribution of cloud occurrence and zonal means of cloud top height is found in a detailed comparison with a climatology for subvisible cirrus clouds from the Stratospheric Aerosol and Gas Experiment II (SAGE II) limb sounder. Overall, validation with various sensors shows the need to consider differences in sensitivity, and especially the viewing geometries and field-of-view size, to make the datasets comparable (e. g. applying integration along the limb path through nadir cloud fields). The simulation of the limb path integration will be an important issue for comparisons with cloud-resolving global circulation or chemical transport models.
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000022370 7001_ $$0P:(DE-Juel1)VDB69255$$aArndt, K.$$b1$$uFZJ
000022370 7001_ $$0P:(DE-HGF)0$$aDudhia, A.$$b2
000022370 7001_ $$0P:(DE-HGF)0$$aHöpfner, M.$$b3
000022370 7001_ $$0P:(DE-Juel1)129125$$aHoffmann, L.$$b4$$uFZJ
000022370 7001_ $$0P:(DE-HGF)0$$aHurley, J.$$b5
000022370 7001_ $$0P:(DE-HGF)0$$aGrainger, R.G.$$b6
000022370 7001_ $$0P:(DE-Juel1)129121$$aGriessbach, S.$$b7$$uFZJ
000022370 7001_ $$0P:(DE-HGF)0$$aPoulsen, C.$$b8
000022370 7001_ $$0P:(DE-HGF)0$$aRemedios, J.J.$$b9
000022370 7001_ $$0P:(DE-Juel1)129145$$aRiese, M.$$b10$$uFZJ
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000022370 7001_ $$0P:(DE-HGF)0$$aSiddans, R.$$b12
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000022370 8567_ $$uhttp://dx.doi.org/10.5194/acp-12-7135-2012
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